• 수산해양기술연구
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• 제12권1호
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• pp.25-30
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• 1976

겨울철 북서태평양인 캄차카 부근 해역에 영향을 주는 저기압의 특성을 종합,분석하고 그 발달기구를 규명하기 위하여 기상월보(1966~1974년) 9닌분과 일본 기상철 발행의 인쇄기일도(1970~1974년)5년분을 사용 분석한 결과를 요약하면 다음과 같다. 1) 겨울철 우리나라 부근에서 발현하는 저기압의 총수는 157개 였다. 이것을 월별로 보면 12월 1월에 각각 48개였고,2월에는 61개 발생했으며 경로별로는 BD경로, 즉 중국에서 발생하여 한국을 통과한 뒤 일본의 북해도로 진입하는 저기압은 총 53개로 전체의 36%로 가장 많았으며, CD경로 즉 대만 부근에서 발생하여 동해를 통과하는 저기압은 총 15개로 전체의 13%로 가장 적었다. 2)저기압 강하도는 A경로 일때가 제일 적었고, CD경로 일때가 가장 컸다. 또한 풍속변화량은 C,CD경로일 대가 최대였고, A경로 일때가 최소였다. 3)저기압이 통과하는 상층에 Jet류가 전일에 비해서 하강, 남하할 경우에는 한기중의 막대한 양이 저기압 후면으로 강하하면, 이에 따르는 위치 에너지의 감량이 저기압을 발달시킨다. 반면에 Jet류가 본래의 상태로 정체하고 있는 경우에는 위치에너지의 변화가 거의 없으므로 저기압은 별로 발달하지 않으며,만일 발달한다고 해도 해면 증발등과 같은 지상조건에 따를 뿐이다. 4)700mb면 등온선의 상층골과 기온극대축(혹은 극소축)의 상관위치 관걔는 저기압 발달에 많은 영향을 준다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.203-203
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• 2016

The linkage between climate change and water security, i.e., the response of water resource to the future climate change, have been of great concern to both scientific community and policy makers. In this study, the impact of future climate on water resources in Yellow River Basin in North of China has been investigated using the Coupled Land surface and Hydrology Model System (CLHMS) and IPCC AR5 projected future climate change in the basin. Firstly, the performances of 14 IPCC AR5 models in reproducing the observed precipitation and temperature in China, especially in North of China, have been evaluated, and it's suggested most climate models do show systematic bias compared with the observation, however, CNRM-CM5、HadCM5 and IPSL-CM5 model are generally the best models among those 14 models. Taking the daily projection results from the CNRM-CM5, along with the bias-correction technique, the response of water resources in Yellow river basin to the future climate change in different emission scenarios have been investigated. All the simulation results indicate a reduction in water resources. The current situation of water shortage since 1980s will keep continue, the water resources reduction varies between 28 and 23% for RCP 2.6 and 4.5 scenarios. RCP 8.5 scenario simulation shows a decrease of water resources in the early and mid 21th century, but after 2080, with the increase of rainfall, the extreme flood events tends to increase.

• Ocean and Polar Research
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• 제43권3호
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• pp.99-111
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• 2021

Occurrence of epiphytic dinoflagellates (EPDs) in coastal waters off Jeju was first reported in 2011 based on 45 substrate samples from 24 macroalgal species. When re-analyzing, the extreme heterogeneous distribution of whole and genus-specific EPDs was reconfirmed across the sampling stations and substrate macroalgal species, as well as even across substrate samples of the same species. Abundance maximum of an EPD genus (cells g-wwt^-1) at a fixed surface-to-volume ratio (SA/V ratio) of the macroalgal species increased as the SA/V ratio increased up to 500 (cm² cm^-3). However, the abundance maximum of Ostreopsis further increased even in the MG2 (morphological group 2) macroalgae with the SA/V ratios over 500. The number of substrate macroalgal species on the plane of the MG and sampling station was more or less evenly scattered than the average EPD abundance, which was primarily driven by Gambierdiscus and Ostreopsis. Of the total EPD abundance of the five stations, 90.6% were represented by the two most common and abundant genera, Gambierdiscus and Ostreopsis, each accounting for 41.6% and 49.0%. Spatially, 95.9% of the total EPD abundance was found in St. 4 and St. 5, of which St. 4 with higher water temperature had more Ostreopsis spp. (31.8%), and St. 5 with higher salinity had more Gambierdiscus spp. (27.3%). Thus, the environmental transition to favorable T-S condition to MG2, the thin filamentous macroalgal group with very high SA/V ratios, is thus likely to support further success in EPD genera led by Ostreopsis in the coastal waters of Jeju.

• Journal of Microbiology and Biotechnology
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• 제31권8호
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• pp.1045-1059
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• 2021

Various abiotic stressors like drought, salinity, temperature, and heavy metals are major environmental stresses that affect agricultural productivity and crop yields all over the world. Continuous changes in climatic conditions put selective pressure on the microbial ecosystem to produce exopolysaccharides. Apart from soil aggregation, exopolysaccharide (EPS) production also helps in increasing water permeability, nutrient uptake by roots, soil stability, soil fertility, plant biomass, chlorophyll content, root and shoot length, and surface area of leaves while also helping maintain metabolic and physiological activities during drought stress. EPS-producing microbes can impart salt tolerance to plants by binding to sodium ions in the soil and preventing these ions from reaching the stem, thereby decreasing sodium absorption from the soil and increasing nutrient uptake by the roots. Biofilm formation in high-salinity soils increases cell viability, enhances soil fertility, and promotes plant growth and development. The third environmental stressor is presence of heavy metals in the soil due to improper industrial waste disposal practices that are toxic for plants. EPS production by soil bacteria can result in the biomineralization of metal ions, thereby imparting metal stress tolerance to plants. Finally, high temperatures can also affect agricultural productivity by decreasing plant metabolism, seedling growth, and seed germination. The present review discusses the role of exopolysaccharide-producing plant growth-promoting bacteria in modulating plant growth and development in plants and alleviating extreme abiotic stress condition. The review suggests exploring the potential of EPS-producing bacteria for multiple abiotic stress management strategies.

• 한국지반신소재학회논문집
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• 제21권4호
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• pp.31-40
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• 2022

최근 건설시장의 다각화와 미래 에너지 자원개발이라는 관점에서 미개발된 에너지 자원(석유, 천연가스 등)이 대량으로 매장되어 있는 극한지(북극권) 개발 사업이 활발히 추진되고 있다. 이러한 지역에서는 극한의 기후로 인한 동토 지반의 침하나 동상 등의 문제가 항상 발생하기 때문에 지반 구조물의 안정성 확보를 위해 열적 특성 분석이 반드시 필요하다. 본 논문에서는 동토 지역에서 지반동결과 관련된 문제들을 평가하고 기술적으로 해결하기 위한 기초 자료 제공을 목적으로, 캐나다 앨버타주 오일샌드 매장 지역의 동토 시료에 대한 열적 특성을 국내 시료와 비교·분석하였다. 일련의 실내 실험을 통해 동결온도에 대한 시간에 따른 부동 수분량을 측정하여 흙의 종류와 동결온도가 부동 수분량에 미치는 영향에 대하여 고찰하였고, 토양의 잠열, 열용량 및 열전도도를 정확하게 파악하기 위하여 동결/비동결 조건에 대한 열전도도 실내 실험을 수행하였다. 실험결과, 동결 완료 후 온도별로 상이한 부동 수분량과 열전도도 특성은 동토 지역 동결온도가 동토의 역학 거동에 영향을 끼칠 수 있음을 규명하였다.

• 분석과학
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• 제36권4호
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• pp.170-179
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• 2023

Starvation, diabetes, alcoholism and hypothermia cause ketoacidosis in the human body; therefore, the cause of death can be determined by analyzing ketone bodies in the blood of the deceased. In the case of decomposition of the cadaver, however, since collecting intact blood is impossible, ketone body analysis is performed using the spleen. However, the index for diagnosing ketoacidosis is based on blood concentration, and its correlation with ketone bodies present in the spleen remains unknown. In particular, since decomposition proceeds rapidly during summer, when temperature and humidity are high, understanding the correlation between ketone bodies in the blood and spleen is important to estimate the state at the time of death from a decaying body. Therefore, in the present study, the correlation between ketone bodies in the blood and spleen of the deceased was explored. Ketone bodies (beta-hydroxybutyric acid [BHB] and acetone) in the blood and spleen were analyzed and compared from autopsies (>100 mg·L^-1 BHB, blood basis) conducted at the Daejeon Forensic Research Institute from June to December 2021. Moreover, the concentration of ketone bodies in the spleen juice and tissues was compared assuming the scenario of extreme decomposition. Ketone retention concentration in the blood and spleen was positively correlated, and the ratio of BHB concentration in the spleen to BHB concentration in the blood ranged from 0.52 to 1.08 (mean = 0.85 ± 0.12), although the ratio may vary depending on the degree of decomposition of the corpse.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.294-294
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• 2022

In 2013, the Asian Development Bank classified the Philippines among the countries facing high food security risks. Evidence has suggested that climate change has affected agricultural productivity, and the effect of extreme climatic events notably drought has worsened each year. This had resulted in serious hydrological repercussions by limiting the timely water availability for the agriculture sector. Laguna is the 3^rd most populated province in the country, and it serves as one of the food baskets that feed the region and nearby provinces. In addition to climate change, population growth, rapid industrialization, and urban encroachment are also straining the delicate balance between water demand and supply. Studies have projected that the province will experience less rainfall and an increase in temperature, which could simultaneously affect water availability and crop yield. Hence, understanding the composite threat of climate change for crop yield and water consumption is imperative to devise mitigation plans and judicious use of water resources. The water footprint concept elaborates the water used per unit of crop yield production and it can approximate the dual impacts of climate change on water and agricultural production. In this study, the water footprint (WF) of six main crops produced in Laguna were estimated during 2010-2020 by following the methodology proposed by the Water Footprint Network. The result of this work gives importance to WF studies in a local setting which can be used as a comparison between different provinces as well as a piece of vital information to guide policy makers to adopt plans for crop-related use of water and food security in the Philippines.

• 한국미생물학회:학술대회논문집
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• 한국미생물학회 2001년도 추계학술대회
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• pp.39-45
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• 2001

Extremophiles are unique microorganisms that are adapted to survive in ecological niches such as high or low temperatures, extremes of pH, high salt concentrations and high pressure. These unusual microorganisms have unique biochemical features which can be exploited for use in the biotechnological industries. Due to the high biodiversity of extremophilic archaea and bacteria and their existence in various biotopes a variety of biocatalysts with different physicochemical properties have been discovered. The extreme molecular stability of their enzymes, membranes and the synthesis of unique organic compounds and polymers make extremophiles interesting candidates for basic and applied research. Some of the enzymes from extremophiles, especially hyperthermophilic marine microorganisms (growth above $85^{\circ}C$), have already been purified in our laboratory. These include the enzyme systems from Pyrococcus, Pyrodictium, Thermococcus and Thermotoga sp. that are involved in polysacharide modification and protein bioconversion. Only recently, the genome of the thermoalkaliphilic strain. Anaerobranca gottschalkii has been completely sequenced providing a unique resource of novel biocatalysts that are active at high temperature and pH. The gene encoding the branching enzyme from this organism was cloned and expressed in a mesophilic host and finally characterized. A novel glucoamylase was purified from an aerobic archaeon which shows optimal activity at $90^{\circ}C$ and pH 2.0. This thermoacidophilic archaeon Picrophilus oshimae grows optimally at pH 0.7 and $60^{\circ}C$. Furthermore, we were able to detect thermoactive proteases from two anaerobic isolates which are able to hydrolyze feather keratin completely at $80^{\circ}C$ forming amino acids and peptides. In addition, new marine psychrophilic isolates will be presented that are able to secrete enzymes such as lipases, proteases and amylases possessing high activity below the freezing point of water.

• Journal of Forest and Environmental Science
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• 제39권2호
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• pp.105-117
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• 2023

Climate change and invasive alien plant species (IAPs) are having a significant impact on mountain ecosystems. The combination of climate change and socio-economic development is exacerbating the invasion of IAPs, which are a major threat to biodiversity loss and ecosystem functioning. Species distribution modelling has become an important tool in predicting the invasion or suitability probability under climate change based on occurrence data and environmental variables. MaxEnt modelling was applied to predict the current suitable distribution of most noxious weed A. adenophora (Spreng) R. King and H. Robinson and analysed the changes in distribution with the use of current (year 2000) environmental variables and future (year 2050) climatic scenarios consisting of 3 representative concentration pathways (RCP 2.6, RCP 4.5 and RCP 8.5) in Bhutan. Species occurrence data was collected from the region of interest along the road side using GPS handset. The model performance of both current and future climatic scenario was moderate in performance with mean temperature of wettest quarter being the most important variable that contributed in model fit. The study shows that current climatic condition favours the A. adenophora for its invasion and RCP 2.6 climatic scenario would promote aggression of invasion as compared to RCP 4.5 and RCP 8.5 climatic scenarios. This can lead to characterization of the species as preferring moderate change in climatic conditions to be invasive, while extreme conditions can inhibit its invasiveness. This study can serve as reference point for the conservation and management strategies in control of this species and further research.

• Communications for Statistical Applications and Methods
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• 제30권2호
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• pp.119-133
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• 2023

With the rapid growth of the economy and fossil fuel consumption, the concentration of air pollutants has increased significantly and the air pollution problem is no longer limited to small areas. We conduct statistical analysis with the actual data related to air quality that covers the entire of South Korea using R and Python. Some factors such as SO₂, CO, O₃, NO₂, PM₁₀, precipitation, wind speed, wind direction, vapor pressure, local pressure, sea level pressure, temperature, humidity, and others are used as covariates. The main goal of this paper is to predict air quality index (AQI) spatio-temporal data. The observations of spatio-temporal big datasets like AQI data are correlated both spatially and temporally, and computation of the prediction or forecasting with dependence structure is often infeasible. As such, the likelihood function based on the spatio-temporal model may be complicated and some special modelings are useful for statistically reliable predictions. In this paper, we propose several methods for this big spatio-temporal AQI data. First, random effects with spatio-temporal basis functions model, a classical statistical analysis, is proposed. Next, neural networks model, a deep learning method based on artificial neural networks, is applied. Finally, random forest model, a machine learning method that is closer to computational science, will be introduced. Then we compare the forecasting performance of each other in terms of predictive diagnostics. As a result of the analysis, all three methods predicted the normal level of PM_2.5 well, but the performance seems to be poor at the extreme value.